Principal / Associate Director – Data Management Engineering

Grade Level (for internal use): 12 The Role: Principal / Associate Director – Data Management Engineering    The Team: The Data Management Engineering team supports critical index data workflows across mastering, ingestion, validation, transformation, and distribution. The team partners globally with Business, Index Operations, QA, Architecture, DevOps, and Infrastructure and values technical ownership, data quality, collaboration, automation, and dependable delivery in a near 24x5 operating environment.  The Impact: This role will help modernize SPDJI’s data management ecosystem through the implementation of NeoXam and broader adoption of Databricks, while maintaining the resilience of existing enterprise data management platforms. The successful candidate will strengthen the quality, scalability, and operational reliability of financial data workflows that support Index Operations and ultimately contribute to accurate and timely index products for global markets.  What’s in it for you:  Play a key role in a strategic transformation involving NeoXam, Databricks, and modern data engineering practices.  Own meaningful, medium-to-large initiatives spanning design, implementation, automation, and operational support.  Collaborate with globally distributed business, operations, architecture, QA, DevOps, and infrastructure teams.  Expand your expertise across financial data mastering, scalable processing, cloud platforms, and CI/CD.

Lead and support the implementation and onboarding of NeoXam for enterprise data management use cases. Design and develop scalable data ingestion, mastering, validation, transformation, and distribution solutions. Translate business and operational requirements into effective technical solutions in partnership with Business, Operations, QA, and Architecture. Support Databricks-based archival, transformation, and large-scale data processing initiatives. Improve data quality, performance, automation, CI/CD, environment management, and operational efficiency. Provide production support for critical financial data workflows and maintain clear technical and operational documentation. What We’re Looking For: Strong SQL Server and T-SQL expertise, including data modeling, database performance optimization, and large-scale data processing. Python development experience for data processing and automation, with exposure to APIs, ETL/data pipelines, and Git/GitHub workflows. Experience with financial data mastering, transformation, validation, reconciliation, and enterprise data management platforms such as NeoXam, Markit EDM, or similar. Experience with Databricks or Lakehouse platforms; exposure to Jenkins, AWS, scripting, workflow schedulers, and environment automation is preferred. Demonstrated ability to independently own medium-to-large data management initiatives and solve complex technical problems.  Strong collaboration and stakeholder-management skills across globally distributed teams.  Clear written and verbal communication, with a disciplined approach to documentation and operational readiness.  Interest in both data engineering and operational automation, with a focus on quality, scalability, and continuous improvement. About S&P Global Dow Jones Indic e s   At S&P Dow Jones Indices, we provide iconic and innovative index solutions backed by unparalleled expertise across the asset-class spectrum. By bringing transparency to the global capital markets, we empower investors everywhere to make decisions with conviction. We’re the largest global resource for index-based concepts, data and research, and home to iconic financial market indicators, such as the S&P 500 ® and the Dow Jones Industrial Average ® . More assets are invested in products based upon our indices than any other index provider in the world. With over USD 7.4 trillion in passively managed assets linked to our indices and over USD 11.3 trillion benchmarked to our indices, our